Arabic Bert Embeddings (from Ebtihal)

Description

Pretrained Bert Embeddings model, uploaded to Hugging Face, adapted and imported into Spark NLP. AraBertMo_base_V1 is a Arabic model orginally trained by Ebtihal.

Download Copy S3 URI

How to use

documentAssembler = DocumentAssembler() \
.setInputCol("text") \
.setOutputCol("document")

tokenizer = Tokenizer() \
.setInputCols("document") \
.setOutputCol("token")

embeddings = BertEmbeddings.pretrained("bert_embeddings_AraBertMo_base_V1","ar") \
.setInputCols(["document", "token"]) \
.setOutputCol("embeddings")

pipeline = Pipeline(stages=[documentAssembler, tokenizer, embeddings])

data = spark.createDataFrame([["أنا أحب شرارة NLP"]]).toDF("text")

result = pipeline.fit(data).transform(data)
val documentAssembler = new DocumentAssembler() 
.setInputCol("text") 
.setOutputCol("document")

val tokenizer = new Tokenizer() 
.setInputCols(Array("document"))
.setOutputCol("token")

val embeddings = BertEmbeddings.pretrained("bert_embeddings_AraBertMo_base_V1","ar") 
.setInputCols(Array("document", "token")) 
.setOutputCol("embeddings")

val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))

val data = Seq("أنا أحب شرارة NLP").toDF("text")

val result = pipeline.fit(data).transform(data)
import nlu
nlu.load("ar.embed.AraBertMo_base_V1").predict("""أنا أحب شرارة NLP""")

Model Information

Model Name: bert_embeddings_AraBertMo_base_V1
Compatibility: Spark NLP 3.4.2+
License: Open Source
Edition: Official
Input Labels: [sentence, token]
Output Labels: [bert]
Language: ar
Size: 410.7 MB
Case sensitive: true

References

  • https://huggingface.co/Ebtihal/AraBertMo_base_V1
  • https://github.com/google-research/bert
  • https://traces1.inria.fr/oscar/
  • https://uokufa.edu.iq/
  • https://mathcomp.uokufa.edu.iq/